T. Anderson Keller

According to our database, T. Anderson Keller authored at least 13 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Deep Generative Models of Music Expectation.

Ninon Lizé Masclef, T. Anderson Keller

CoRR, 2023

Flow Factorized Representation Learning.

Yue Song, T. Anderson Keller, Nicu Sebe, Max Welling

CoRR, 2023

Traveling Waves Encode the Recent Past and Enhance Sequence Learning.

T. Anderson Keller, Lyle Muller, Terrence J. Sejnowski, Max Welling

CoRR, 2023

DUET: 2D Structured and Approximately Equivariant Representations.

Xavier Suau, Federico Danieli, T. Anderson Keller, Arno Blaas, Chen Huang, Jason Ramapuram, Dan Busbridge, Luca Zappella

Proceedings of the International Conference on Machine Learning, 2023

Latent Traversals in Generative Models as Potential Flows.

Yue Song, T. Anderson Keller, Nicu Sebe, Max Welling

Proceedings of the International Conference on Machine Learning, 2023

Neural Wave Machines: Learning Spatiotemporally Structured Representations with Locally Coupled Oscillatory Recurrent Neural Networks.

T. Anderson Keller, Max Welling

Proceedings of the International Conference on Machine Learning, 2023

2022

Homomorphic Self-Supervised Learning.

T. Anderson Keller, Xavier Suau, Luca Zappella

CoRR, 2022

2021

Modeling Category-Selective Cortical Regions with Topographic Variational Autoencoders.

T. Anderson Keller, Qinghe Gao, Max Welling

CoRR, 2021

As easy as APC: Leveraging self-supervised learning in the context of time series classification with varying levels of sparsity and severe class imbalance.

Fiorella Wever, T. Anderson Keller, Victor Garcia, Laura Symul

CoRR, 2021

Topographic VAEs learn Equivariant Capsules.

T. Anderson Keller, Max Welling

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Self Normalizing Flows.

T. Anderson Keller, Jorn W. T. Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling

Proceedings of the 38th International Conference on Machine Learning, 2021

Predictive Coding with Topographic Variational Autoencoders.

T. Anderson Keller, Max Welling

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

2018

Fast Weight Long Short-Term Memory.

T. Anderson Keller, Sharath Nittur Sridhar, Xin Wang

CoRR, 2018